The present invention relates to automatic spinal canal segmentation in medical image data, and more particularly, to automatic spinal canal segmentation in computed tomography images using cascaded random walks.
Segmentation of the spinal canal in medical image data is an important task because it facilitates analysis, diagnosis, and therapy planning related to spines. Segmentation of the spinal canal provides helpful references to parcellate other anatomical structures and contributes to the understanding of full-body medical image scans. Given the spinal canal, it is much easier to delineate the spinal cord, which is vulnerable to dosage tolerance and crucial for radiotherapy.
Conventional techniques for segmentation of the spinal cord or spinal canal typically focus on magnetic resonance (MR) images, at least in part due to the better capability of MR images in rendering soft tissues, as compared to other medical imaging modalities. However, such techniques cannot accurately segment the spinal canal in low-resolution, low-contrast computed tomography (CT) images.